Fast query point movement techniques with relevance feedback for content-based image retrieval

    Authors

    D. Z. Liu; K. A. Hua; K. Vu;N. Yu

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Keywords

    Computer Science, Information Systems; Computer Science, Software; Engineering; Computer Science, Theory & Methods

    Abstract

    Target search in content-based image retrieval (CBIR) systems refers to finding a specific (target) image such as a particular registered logo or a specific historical photograph. Existing techniques were designed around query refinement based on relevance feedback, suffer from slow convergence, and do not even guarantee to find intended targets. To address those limitations, we propose several efficient query point movement methods. We theoretically prove that our approach is able to reach any given target image with fewer iterations in the worst and average cases. Extensive experiments in simulated and realistic environments show that our approach significantly reduces the number of iterations and improves overall retrieval performance. The experiments also confirm that our approach can always retrieve intended targets even with poor selection of initial query points and can be employed to improve the effectiveness and efficiency of existing CBIR systems.

    Journal Title

    Advances in Database Technology - Edbt 2006

    Volume

    3896

    Publication Date

    1-1-2006

    Document Type

    Article

    Language

    English

    First Page

    700

    Last Page

    717

    WOS Identifier

    WOS:000237081600042

    ISSN

    0302-9743; 3-540-32960-9

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